Year 2200

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DISTRIBUTION OF FUTURE SEA LEVEL RISE (em)

Figure 6,2. Plots showing the probability of various rises of sea level in the years 2030, 2100, and 2200, calculated on the basis of the Monte Carlo estimation technique, combining experts* probability distributions for model parameters. From Titus and Narayanan, 1W4.

of persons displaced from coastal flooding), the Carnegie Mellon group offered its results only as illustrative of the capability of IA techniques. Its numerical results have meaning only after the range of physical, biological, and social outcomes and their costs and benefits have been quantified - a Herculean task. Similar studies have been made in Holland by a Dutch effort to produce integrated assessments for policy makers. Jan Rotmans, who headed one of the efforts, likes to point out that such modeling of complex physical, biological, and social factors cannot produce credible "answers" to current policy dilemmas but can provide "insights11 to policy makers that will put decision making on a stronger analytical basis (Rotmans and van Asselt, 1996). Understanding the strengths and weaknesses of any complex analytic tool is essential to rational policy

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milking, even if quantifying the costs and benefits of specific activities is controversial (e.g., Schneider, 1997b).

William Nordhaus, an economist from Yale University, has taken heroic steps to put the climatic change policy debate into an optimizing framework. He is an economist who has long acknowledged that an efficient economy must internalize externalities (in other w ords, find the full social costs of our activities and not only the direct cost reflected in conventional "free market11 prices to private firms or individuals). He tried to quantify this external damage from climate change and then tried to balance it against the costs to the global economy of policies designed to reduce CO2 emissions. His "optimized" solution was a carbon tax, designed to internalize 1 he externality of damage to the climate by increasing the price of fuels in proportion to how much carbon they emit, thereby providing an incentive for society to use less of these fuels - in essence, a Upollutor pays" principle.

Nordhaus (1992) imposed carbon tax scenarios ranging from a few dollars per ton to hundreds of dollars per ton of carbon emitted; the latter would effectively limit coal use in ihe world economy, I le showed that, 111 the context of his model and its assumptions, these carbon emission fees would cost the world economy anywhere from less than 1%

m m annual loss in gross national product (GNP) to a several percent loss by the year 2100. The efficient, optimized solution from classical economic cost-benefit analysis is thai carbon taxes should be levied sufficient to reduce the GNP as much as it is worth to avert climate change (e.g., the damage to GNP from climate change). I le assumed that the impacts of climate change were equivalent to a loss of about 1% of GNP This led to an "optimized" initial carbon tax of about five dollars or so per ton of carbon dioxide emitted, rising by scvcralfold to AD. 2l()0. In the context of his modeling exercise, this would avert only a few tenths of a degree of global warming to the year 2 KM), a very small fraction of the 4 °C warming his model projected.

How did Nordhaus arrive at climate damage being about 1% of GNP? I le assumed that agriculture was the economic market sector most vulnerable to climate change. Tor decades, agronomists had calculated potential changes to crop yields from various climate change scenarios, suggesting some regions, now too hot, would sustain heavy losses from warming, whereas others, now too cold, could gain. Noting that the United States lost about one-third of its agricultural economy in the heat waves of 1988, and that agriculture then represented about 3% of the U.S. GNP, Nordhaus thought the typically projected climatic changes might thus cost the U.S. economy something like 1% annually in the 21st century. I his figure was severely criticized because it neglected damages from health impacts (e.g., expanded areas of tropical diseases, heat-stress deaths, etc.), losses from coastal fltxxling or severe storms, security risks from the presence of "boat people" as the result of coastal disruptions in South Asia, or any damages to wildlife (e.g., Sorenson et al., 1998), fisheries, or ecosystems (e.g., IPCC, 1996b) that would almost surely accompany temperature rises at rates of degrees per century as are ty pically projected. It also was criticized because Nordhaus^s estimate neglected potential increases in crop or forestry yields from the direct effects of increased CO2 in the air on the photosynthetic response of these marketable plants. Nordhaus responded to his critics by conducting a survey, similar to that undertaken by Morgan

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